A new software prepared by researchers from MIT will allow photographers to keep only the best images by using an algorithm instead of them having to go through hundreds of images by themselves.

The ‘MemNet’ algorithm produced by scientists from the Massachusetts Institute of Technology (MIT) can identify images in terms of different degrees of being memorable or forgettable. More interestingly, it can do so with as much accuracy as humans can.

The software indicates how likely someone will recall a visual message, explains one of the MIT researchers, Aditya Khosla.

With the help of deep learning techniques and a neural network, MemNet can detect image patterns as per their memorability, when incorporated into systems, according to Khosla, can make the latter capture the “most important information”.

Tens of thousands of images that were previously ranked according to their memorability were fed to the algorithm which then independently examined the pictures and learned how to detect patterns and links among them. It was able to make the distinction between these and those images deemed forgettable.

Furthermore, the software can also generate a heat map on images to denote the parts thereof that make of them distinctly memorable.

MemNet was found to be as accurate as humans when the researchers tested it against human subjects to determine which group would perform better at forecasting how another group of individuals would be successful at remembering images they had never seen before. Humans, though, are slightly better at predicting human memorability (they scored 68 % while the algorithm scored 64 %).

The team is proud of the feat they achieved.

“While deep-learning has propelled much progress in object recognition and scene understanding, predicting human memory has often been viewed as a higher-level cognitive process that computer scientists will never be able to tackle. Well, we can, and we did!” exclaimed one of the authors, Aude Oliva.

They now wish to use their algorithm for future practical applications. For instance, they think it might be used in apps that can tweak pictures to render them more memorable. Furthermore, their research might be useful in other fields of study as well: it could help understand how human memory works.